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ABDAL MOHAMEDBSc in Artificial Intelligence and Computer ScienceBSc in Artificial Intelligence and Computer Science1.History of AI in Racing Games2.Neural Networks in GamesSectionsBSc in Artificial Intelligence and Computer ScienceBSc in Artificial Intelligence and Computer ScienceHistoryGran Trak 10Single-player racing arcade game released byAtari in 1974Did not have any AIPole

PositionSingle- player racing game released by Namcoin 1982Considered first racing game with AI

BSc in Artificial Intelligence and Computer ScienceHistorySuper Mario KartAddition of Power UpsReleased in 1992 for theSuperNintendo Entertainment System.Driver

Free- form World1998 video game developed byReflections InteractiveVehicular Combat: Power Ups + Free Form WorldBSc in Artificial Intelligence and Computer ScienceSimple Areas of AI in Racing Games1.SteeringSort of Basic

Used in Formula One-Built to win, GTA32001for background animation purpose.2. PathfindingBecomes more free-form worldWould need to make decision on whereto go.Need to find the best path between twopoints, avoiding any obstacles.BSc in Artificial Intelligence and Computer ScienceSteering + Racing LinesRacing Lines methods was used extensively until there was CPU powerto do something else.It is just a drawn line in which the cars follow that line or stuck to thatline.It uses Spline, where addition information such as velocity isincluded.AdvantageIt is very easy to create cheap spine creation toolDisadvantageVery limited- and gets very difficultNot very realistic- as car follows line, no response to deflectionBSc in Artificial Intelligence and Computer SciencePathfinding + Tactical AIRacing line does not really work withfree-form world so one of the solutionsis having set path to where the car/character is fleeing.Many different types of pathfindingproblem exist. Unfortunately, no onesolution is appropriate to every type ofpathfinding problem. The solutiondepends on the specifics of thepathfinding requirements for anygiven game. For example, is thedestination moving or stationary?Pathfinding are becoming the mainand popular issue in gamingindustries.Tactical AI involves decisionmaking . For example, policecars trying to create roadblocks, where the path wouldgo, in ways the character didnot see it coming.BSc in Artificial Intelligence and Computer ScienceBSc in Artificial Intelligence and Computer ScienceNeural NetworksNeural Network are capable of learning and improving theirperformance with their previous experience.Artificial network used in games are quite simple in comparison tohuman brain. For many applications artificial neural networks arecomposed of only a handful, a dozen or so, neurons.This is far simpler than our brain. Some specific application usenetworks composed of perhaps thousands of neurons, yet even theseare simple in comparison to our brain as they contain about 10¹¹neurons.The network itself is a function giving a unique set of output for thegiven input.BSc in Artificial Intelligence and ComputerScienceUses of Neural Networks inGamesFor game, neural networks offer some key advantages over moretraditional AI techniques.First, using a neural networks enables game developers to simplifycoding of complex state machines or rule-based systems by relegatingkey decision making processes to one or more trained neural networks.Second, neural networks offer the potential for the game’s AI to adaptas the game is played. This is rather compelling possibility and is a verypoplar subject in the game AI community.In spite of these advantages, neural networks have not gainedwidespread use in video games. Game developers have used neuralnetworks in some popular games; but by and large, their use in gamesis limited. This probably is due to several factors, of which is describednext.BSc in Artificial Intelligence and Computer ScienceLimitation of Neural NetworksFirst, neural networks are great at handling highly nonlinear problems;once you cannot tackle easily using traditional methods. Thissomething makes understanding exactly what the networks is doingand how it is arriving at its result difficult to follow.Second, it’s difficult at times to predict what a neural network willgenerate as output, especially if the network is programmed to learn oradapt within a game.These two factors make testing and debugging a neural networkrelatively difficult compared to testing and debugging a finite statemachine, for example.BSc in Artificial Intelligence and Computer ScienceArtificial Neural Networks in racing car game Videohttp://www.youtube.com/watch?v=QSP36H8_AbUhttp://www.youtube.com/watch?v=FKAULFV8tXwBSc in Artificial Intelligence and Computer ScienceReferences/ Bibliographyhttp://en.wikipedia.org/wiki/Special:Search?search=http://www.google.co.uk/http://www.cs.bham.ac.uk/~jab/Modules/IntroAI/07-08/index.htmlDr Nick Hawes's Guest Lecture on AI IN COMPUTER GAMES.http://uk.youtube.com/http://togelius.blogspot.com/2006/04/evolutionary-car-racing-videos.htmlAI for Game DevelopersBy David M. Bourg, Glenn SeemannBSc in Artificial Intelligence and Computer ScienceThe End